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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Earth-Abundant Manganese Nitride Catalysts for Mild-Condition Ammonia Synthesis

Developing advanced catalytic materials for mild-condition ammonia (NH 3 ) synthesis is essential for improving the energy efficiency of the industrial Haber-Bosch process. Here, in this study, we report a ζ-phase manganese nitride (MnN 0.43 ) catalyst for low-temperature NH 3 synthesis. The as-synthesized MnN 0.43 catalyst is protected by a carbon shell, allowing for the storage and processing of the air-sensitive metal nitride under ambient conditions. After activation in situ, the MnN 0.43 catalyst exhibits high activity for NH 3 synthesis at 250–350 °C, surpassing the conventional noble metal based Ru/MgO catalyst. A combination of kinetic, chemisorption, isotope labeling and computational studies indicate that a nitrogen vacancy-mediated associative mechanism accounts for the catalytic enhancements. Our work highlights the great potential of earth-abundant transition metal nitrides for catalyzing mild-condition NH 3 synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Electrocatalytic Ammonia Oxidation with Coordinatively Saturated Ruthenium Catalyst

This communication describes the investigation of a coordinatively saturated complex [Ru(tpy)(dmabpy)Cl] + ([Ru(Cl)] + ) as an ammonia oxidation catalyst. Cyclic voltammetry measurements show an ideal S-shaped wave, indicating total catalysis conditions with a k obs (TOF max ) of 9360 h −1 . The reaction was found to be first-order in [Ru(Cl)] + and third-order in [NH 3 ]. Stoichiometric reactions of the one-electron oxidized species, [Ru(Cl)] 2+ , were monitored following the addition of 15 NH 3 using 1 H and 15 N NMR spectroscopy. These experiments showed that the chloride-coordinated complex rapidly converts NH 3 to N 2 . NMR spectroscopy and electrochemistry results definitively show that NH 3 does not substitute the Cl − ligand to form the previously reported [Ru(NH 3 )] 2+ catalyst which operates by a different mechanistic pathway. Taken together these results indicate outersphere electron transfer mediated ammonia oxidation reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2004

Lunar and Planetary Science XXXV: Outer Solar System

The session 'Outer Solar System" inlcuded:Monte Carlo Modeling of [O I] 630 nm Auroral Emission on Io; The Detection of Iron Sulfide on Io; Io and Loki in 2003 as Seen from the Infrared Telescope Facility Using Mutual Satellite and Jupiter Occultations; Mapping of the Zamama-Thor Region of Io; First Solar System Results of the Spitzer Space Telescope; Mapping the Surface of Pluto with the Hubble Space Telescope; Experimental Study on Fischer-Tropsch Catalysis in the Circum-Saturnian Subnebula; New High-Pressure Phases of Ammonia Dihydrate; Gas Hydrate Stability at Low Temperatures and High Pressures with Applications to Mars and Europa; Laboratory UV Photolysis of Planetary Ice Analogs Containing H2O + CO2 (1:1); The OH Stretch Infrared Band of Water Ice and Its Temperature and Radiation Dependence; Band Position Variations in Reflectance Spectra of the Jovian Satellite Ganymede; Comparison of Porosity and Radar Models for Europa s Near Surface; Combined Effects of Diurnal and Nonsynchronous Surface Stresses on Europa; Europa s Northern Trailing Hemisphere: Lineament Stratigraphic Framework; Europa at the Highest Resolution: Implications for Surface Processes and Landing Sites; Comparison of Methods to Determine Furrow System Centers on Ganymede and Callisto; Resurfacing of Ganymede by Liquid-Water Volcanism; Layered Ejecta Craters on Ganymede: Comparisons with Martian Analogs; Evaluation of the Possible Presence of CO2-Clathrates in Europa s Icy Shell or Seafloor; Geosciences at Jupiter s Icy Moons: The Midas Touch; Planetary Remote Sensing Science Enabled by MIDAS (Multiple Instrument Distributed Aperture Sensor); and In Situ Surveying of Saturn s Rings.

Source record↗
DOE OSTI2025

Temperature-dependent solid electrolyte interphase reactions drive performance in lithium-mediated nitrogen reduction to ammonia

The solid electrolyte interphase (SEI) is a vital component to control mass transport and selectivity in the lithium-mediated reduction of N 2 to NH 3 (Li-N 2 R). Finding strategies that generate the optimal SEI, a complex network of organic and inorganic species, can potentially improve Li-N 2 R performance. Here, we unravel structure-property relationships of the SEI by correlating its composition with the NH 3 faradaic efficiency (FENH3). By modifying the reaction temperature, we alter electrolyte decomposition reactions and observe changes in the SEI that explain FE NH3 trends between electrolyte solvents. We quantify a complex reaction environment at elevated temperatures where SEI formation is counteracted by etching reactions. This tradeoff leads to temporal fluctuations of FE NH3 , but the maximal FE NH3 can reach up to 40%, the highest value reported for batch cells at ambient pressure, thus far. In conclusion, our work underscores the potential of novel electrolytes that steer SEI selectivity and, ultimately, improve Li-N 2 R performance.

electrocatalytic nitrogen reduction↗
DOE OSTI2025

Python Library for Monte Carlo Simulations with Ab Initio and Machine-Learned Interatomic Potentials

There is a growing need in the simulation community for software that provides a transparent, reproducible, usable, and extensible (TRUE) Monte Carlo (MC) simulation framework employing energies from ab initio methods and machine-learning interatomic potentials (MLIPs). We introduce a Python library (ASE-MC) that adds Monte Carlo functionality to the Atomic Simulation Environment (ASE) package. Now, we can combine the powerful tools used to build systems and perform ab initio and MLIP in ASE with MC simulation algorithms to sample the configurational space with a concise Python script. After presenting the design philosophy, we demonstrate the flexibility of our approach using selected examples. These example simulations include liquid water described with a message-passing MLIP in the canonical and isothermal–isobaric ensembles, sampling the characteristic dihedral angle of biphenyl and comparing an MLIP to first-principles calculations, and a grand canonical Monte Carlo simulation of ammonia adsorption on Pt(111). These examples showcase the main features of the software, which include flexibility in the choice of ab initio or MLIP engine, ab initio or MLIP grand canonical MC with cavity bias insertions and deletions, the ability to add custom MC moves to the move set, and how users can condense complex MC workflows into a single Python script. Finally, this library serves as a framework for reproducible Monte Carlo simulations, facilitating easy reproduction of the work and application to new systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Exploration of Electronic and Magnetic Properties of Ceria for Applications of Microwave Assisted Catalysis

This was presented at APS Global Physics Summit 2025 in Anaheim, CA. This study focuses on characterizing how vacancies and other dopants influence the electronic and magnetic properties of ceria and exploring the potential mechanisms by which these properties affect or control its catalytic behavior under microwave radiation. By examining ceria’s electronic response to external electromagnetic fields, specifically magnetic fields within the microwave range, the work aims to uncover insights into how microwaves might optimize catalytic effects. The study also includes a comparative analysis of different functionals to refine understanding of ceria’s electronic behavior and catalytic efficacy in these applications.

ammonia synthesis↗
DOE OSTI2026

Multi‐Scale Model‐Informed Deep Learning for Plasma‐Nanoparticle Interaction

The Overarching Goal of this proposed research is to understand and quantitively determine the interactions between non-thermal plasma (hot electrons, reactive radicals, vibrationally excited species) and surface reactions on influencing the activity and selectivity of the desired reactions via developing multi-scale model informed deep learning algorithm. Investigating non-thermal plasma-surface interaction is feasible due to the low bulk temperature in the discharge region. To investigate the role of plasma-nanoparticle interaction on enhancing the reaction kinetics, we will focus on ammonia cracking to generate clean hydrogen over earth-abundant, non-critical metallic nanoparticles, which is of great significance for decarbonization. We hypothesize that (1) reactive radicals interacting with surface reaction species via Eley–Rideal mechanism will significantly lower the energetics of the potential rate-limiting step of nitrogen formation; (2) the surface will be charged heterogeneously under non-thermal plasma conditions and the charged site will lower the energetics of ammonia cracking through Langmuir– Hinshelwood mechanism; (3) vibrationally excited ammonia will further promote the initial N-H bond cleavage. To access the hypothesis, we will (1) reveal the surface charge effects on tunning the reaction energetics via interpretable, physics-informed deep learning accelerated density functional theory (DFT) calculations; (2) determine the reactive radicals interacting with surface reaction species on tuning the reaction energetics via DFT; (3) reveal the surface charge effects on tunning the reaction energetics via DFT and deep learning models, (4) quantify how vibrationally excited species, reactive radicals, and surface charging effects on enhancing the catalysis via developing DFT-based microkinetic modeling (MKM) and active learning. Deep and active learning of plasma-nanoparticle interactions effects on enhancing ammonia cracking to generate hydrogen represents a new paradigm for designing high performance plasma materials. The fundamental science of how plasma-nanoparticle interactions will change the plasma kinetics and will improve the energy efficiency for decarbonization and sustainability. The interpretable and physics-informed machine learning model will accelerate low temperature plasma chemistry and material discovery with physics rules and model interpretation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Atmospheric-pressure ammonia synthesis on AuRu catalysts enabled by plasmon-controlled hydrogenation and nitrogen-species desorption

The Haber–Bosch process for ammonia synthesis contributes up to ~3% of global greenhouse gas emissions. Plasmonic catalysts strongly concentrate light and can alter the reaction intermediates via out-of-equilibrium processes, providing the potential for an alternative, less-energy-intensive pathway to synthesize ammonia. Here, in this study, we show that gold-ruthenium (AuRu) bimetallic nanoparticles can synthesize ammonia at room temperature and pressure using visible light. We create AuRu alloys with varying compositions and achieve ammonia production rates of ~60 μmol per gram of catalyst bed per hour. In situ infrared spectroscopy reveals that light accelerates the hydrogenation of nitrogen intermediates compared to conventional thermal catalysis. Through computational modelling, we demonstrate that photo-excited electrons enable associative hydrogenation pathways for nitrogen activation rather than direct nitrogen–nitrogen bond breaking. This light-assisted mechanism requires both hydrogen and light working together to overcome the nitrogen activation barrier, mimicking how biological enzymes produce ammonia naturally and providing fundamental insights for developing sustainable, energy-efficient chemical synthesis.

Yuan, Lin [Stanford Univ., CA (United States)] (OR↗
DOE OSTI2024

Adaptive tau-leaping methods for microscopic-lattice kinetic Monte Carlo simulations

Traditional Kinetic Monte Carlo (KMC) approaches, rooted in Gillespie’s stochastic simulation algorithm, become computationally demanding in systems with a large range of timescales. The goal of this work is to propose and study new adaptive lattice-KMC time integration strategies for spatially non-uniform systems. To that end, two novel adaptive tau-leaping methods and their corresponding time integration strategies are developed based on the idea of the “n-fold” direct KMC method. These strategies allow for the simultaneous execution of multiple reactions, advancing time by adaptively selected coarse increments. We present numerical experiments comparing the proposed methods with existing approaches in a catalytic surface kinetics application involving ammonia decomposition.

Bimolecular reactions↗
DOE OSTI2024

Enhancing Nitrogen Activation in Electrochemical Reduction: The Role of Rare Earth Oxide Surface Configurations

The pursuit of sustainable ammonia synthesis has prompted the exploration of ambient electrochemical nitrogen reduction reaction (e-NRR) as an alternative to the energy-intensive Haber-Bosch process. Here, this study conducted a theoretical investigation into the use of rare earth oxide materials, specifically dysprosium oxide (Dy 2 O 3 ), as potential electrocatalysts for NRR. Utilizing spin-polarized density functional theory calculations, we explored the interaction between Dy 2 O 3 surfaces and nitrogen (N 2 ) molecules, examining the capability of Dy 2 O 3 to adsorb and activate N 2 under ambient conditions. The results indicate that Dy 2 O 3 surfaces exhibit diverse configurations and bonding environments, providing a variety of reactive sites that display different behaviors in N 2 adsorption and activation. The distinctive electronic structure and surface chemistry of a particular Dy 2 O 3 surface configuration were found to significantly enhance the activation of N 2 by promoting charge transfer, which facilitates the NRR process. This research provides deep insights into the mechanistic pathways of N 2 reduction over Dy 2 O 3 , highlighting the surface properties as pivotal in catalysis. These theoretical insights serve as a foundation for the development of novel rare earth-based electrocatalytic materials for efficient ambient e-NRR, potentially transforming ammonia production into a greener and more energy-efficient process.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Diffusion Model-Guided Inverse Design of Bimetallic Catalysts for Ammonia Decomposition

In the past decade, artificial intelligence and deep learning have played increasingly prominent roles in materials design and discovery. Among these, generative AI models, known for their ability to create unique and complex structures, have emerged as state-of-the-art tools for materials screening due to their high efficiency and low computational cost. In catalysis, one of the major challenges is identifying promising material candidates within an immense chemical space. This challenge can be addressed using generative approaches, such as diffusion-based inverse design models. In this study, we present a machine learning-guided workflow that employed a diffusion model for the inverse design of bimetallic alloy catalysts for low-carbon ammonia decomposition, a key reaction for ammonia emission control and sustainable hydrogen production. Catalyst candidates were evaluated using nitrogen adsorption energy as the key descriptor, inspired by multiscale modeling. The proposed workflow identified low-cost, environmentally friendly catalysts with excellent catalytic performance, which have been validated theoretically and experimentally. Our framework decoupled the generative and property-prediction components, enhancing both flexibility and accuracy in the catalytic material design process.

Adsorption↗
DOE OSTI2026

Group-Additivity–Embedded Multiscale Modeling for Electric Field-Enhanced Nanocatalysis

Elucidating structure-performance relationships remains a central challenge in field-enhanced catalysis, where nanoparticles exhibit nonuniform surface sites with site-dependent responses to electric fields. Low-coordination sites (edges, corners, and tips) are particularly electric field-sensitive (EF), leading to nonuniform charge distribution, adsorption energies, and catalytic activity. Here, using ammonia decomposition on a ruthenium cluster as a model system, we develop a transferable multiscale framework integrating density functional theory, group additivity (GA), Brønsted-Evans-Polanyi scaling, and microkinetic modeling to predict EF-dependent activity across nonuniform cluster sites. Across sites and fields, the nitrogen adsorption energy (E N ) emerges as the governing descriptor, yielding robust volcano relationships whose optimum shifts systematically with field: negative fields strengthen N binding via electron accumulation, while positive fields weaken N binding via charge depletion, moving the optimal E N toward weaker binding. Microkinetic analysis shows that N≡N bond formation remains the key kinetic bottleneck over most conditions; positive fields lower the effective barrier and, critically, increase the fraction of near-optimal active sites, leading to a net enhancement in overall activity relative to zero-field and negative-field cases. By capturing EF- and site-dependent energetics with high accuracy and low computational cost, this GA-embedded multi-scale simulation workflow provides a physically interpretable route to predict and design field-enhanced nanocatalysis.

ammonia decomposition↗
NASA NTRS1999

Formation of Amino Acid Thioesters for Prebiotic Peptide Synthesis: Catalysis By Amino Acid Products

The origin of life can be described as a series of events in which a prebiotic chemical process came increasingly under the control of its catalytic products. In our search for this prebiotic process that yielded catalytic takeover products (such as polypeptides), we have been investigating a reaction system that generates peptide-forming amino acid thioesters from formaldehyde, glycolaldehyde, and ammonia in the presence of thiols. As shown below, this model process begins by aldol condensation of formaldehyde and glycolaldehyde to give trioses and releases. These sugars then undergo beta-dehydration yielding their respective alpha-ketoaldehydes. Addition of ammonia to the alpha-ketoaldehydes yields imines which can either: (a) rearrange in the presence of thesis to give amino acid thioesters or (be react with another molecule of aldehyde to give imidazoles. This 'one-pot' reaction system operates under mild aqueous conditions, and like modem amino acid biosynthesis, uses sugar intermediates which are converted to products by energy-yielding redox reactions. Recently, we discovered that amino acids, such as the alanine reaction product, catalyze the first and second steps of the process. In the presence of ammonia the process also generates other synthetically useful products, like the important biochemical -- pyruvic acid.

Weber, Arthur L.↗
DOE OSTI2024

Pd-Ru pair on Pt surface for promoting hydrogen oxidation and evolution in alkaline media

Hydrogen oxidation reaction in alkaline media is critical for alkaline fuel cells and electrochemical ammonia compressors. The slow hydrogen oxidation reaction in alkaline electrolytes requires large amounts of scarce and expensive platinum catalysts. While transition metal decoration can enhance Pt catalysts’ activity, it often reduces the electrochemical active surface area, limiting the improvement in Pt mass activity. Here, we enhance Pt catalysts’ activity without losing surface-active sites by using a Pd-Ru pair. Utilizing a mildly catalytic thermal pyrolysis approach, Pd-Ru pairs are decorated on Pt, confirmed by extended X-ray absorption fine structure and high-angle annular dark-field scanning transmission electron microscopy. Density functional theory and ab-initio molecular dynamics simulations indicate preferred Pd and Ru dopant adsorption. The Pd-Ru decorated Pt catalyst exhibits a mass-based exchange current density of 1557 ± 85 A g –1 metal for hydrogen oxidation reaction, demonstrating superior performance in an ammonia compressor.

25 ENERGY STORAGE↗
NASA NTRS2022

Structures of the Nitrogenase Complex Prepared Under Catalytic Turnover Conditions

The enzyme nitrogenase couples adenosine triphosphate (ATP) hydrolysis to the multielectron reduction of atmospheric dinitrogen into ammonia. Despite extensive research, the mechanistic details of ATP-dependent energy transduction and dinitrogen reduction by nitrogenase are not well understood, requiring new strategies to monitor its structural dynamics during catalytic action. Here, we report cryo–electron microscopy structures of the nitrogenase complex prepared under enzymatic turnover conditions. We observe that asymmetry governs all aspects of the nitrogenase mechanism, including ATP hydrolysis, protein-protein interactions, and catalysis. Conformational changes near the catalytic iron-molybdenum cofactor are correlated with the nucleotide-hydrolysis state of the enzyme.

Hannah L. Rutledge↗
DOE OSTI2026

Unveiling the mechanism of lithium-mediated nitrogen reduction via operando X-ray scattering in a flow cell with hydrogen oxidation

The lithium-mediated nitrogen reduction reaction (Li-NRR) is currently the most promising strategy for electrochemical ammonia synthesis. In this study, we present an operando grazing incidence wide angle X-ray scattering (GI WAXS) investigation using an improved electrochemical flow cell that enables hydrogen oxidation at the anode and thereby eliminates the need of a sacrificial proton donor. The improved cell design also increases nitrogen availability and mass transport, achieving ammonia faradaic efficiencies (FEs) up to 36%. This setup allows direct analysis of reaction intermediates and the solid electrolyte interphase (SEI) using state-of-the-art diglyme-based electrolytes. We identify lithium amide (LiNH2) as the only stable, crystalline intermediate, providing direct insight into the Li-NRR mechanism. Notably, in diglyme-based electrolytes, the SEI composition differs significantly from that in tetrahydrofuran-based systems, with reduced LiF content and the formation of previously unreported crystalline diglyme–lithium salt complexes. These species likely influence ammonia selectivity and long-term stability. Our findings highlight how the electrolyte composition and cell architecture govern Li-NRR selectivity and efficiency, offering a foundation for the rational design of next-generation SEI layers and solid electrolytes to enable scalable electrochemical ammonia synthesis.

Deissler, Niklas H. [Technical Univ. of Denmark, L↗